Impact of bacterial and fungal inoculants on the resident rhizosphere microbiome and the volatilome of tomato plants under leaf herbivory stress

Abstract Various studies have addressed the impact of microbial inoculants on the composition of the resident microbiome. How microbial inoculants impact plant metabolism and interact with the resident rhizobiota under herbivory stress remains elusive. Here, we investigated the impact of two bacterial and two fungal inoculants, inoculated as single species and as a synthetic community, on the rhizosphere microbiome and volatilome of tomato plants (Solanum lycopersicum) comparing nonstress conditions to exposed to leaf herbivory by Spodoptera exigua. Based on amplicon sequencing analysis, rhizobacterial community composition was significantly affected by all four inoculants and the magnitude of this effect was dependent on herbivory stress. Fungal community composition was altered by the microbial inoculants but independent of herbivory stress. The rhizosphere volatilome was impacted by the microbial inoculation and differences between treatments were evened under herbivory stress. Each microbial inoculant caused unique changes in the volatilome of stressed plants but also shared similar responses, in particular the enhanced production of dimethyl disulfide and benzothiazole. In conclusion, the introduction of microbial inoculants in the tomato rhizosphere caused unique as well as common changes in the rhizosphere microbiome and volatilome, but these changes were minor compared to the microbiome changes induced by herbivory stress.


Introduction
In the current agricultural scheme, there is a great need for sustainable alternatives to chemical pesticides and fertilizers.In this context, plant-beneficial micr obes ar e consider ed an envir onmentall y friendl y alternativ e for impr oving plant health and defense (Finkel et al. 2017 ).Microbial inoculants typically contain a strain of specific plant-associated beneficial bacterial or fungal species.Inoculation consists of introducing the microbes into the soil or onto planting materials, for example, by seed coating, root dipping, or soil dr enc hing.Ho w e v er, the potential use of microbial inoculants is still questioned due to their variable efficacy under field conditions.Also, the mechanisms underlying their ecological interactions with soil microbes and the host plant are largely unknown.P articularl y for the root-or soil-inoculated microbes, successful rhizosphere colonization is crucial for the establishment of a beneficial relationship with the plant (Romano et al. 2020 ).To ac hie v e a sufficient colonization le v el, differ ent str ategies ar e often follo w ed to impr ov e micr obial surviv al and ada ptation to the pr e v ailing natur al conditions .T hese include the introduction of high numbers of bacterial or fungal cells (often higher than 10 7 cells/g), elaborating on specific formulations, or repeated applications (Kaminsky et al. 2019 ).Another a ppr oac h is to a ppl y ben-eficial microbes as a combination of different species (known as microbial consortia or synthetic communities).This is considered mor e adv anta geous than the a pplication of single str ains due to potential synergies in their effects on plant protection or microbial persistence in the environment (Bradá čová et al. 2019b ).Another factor influencing the success of microbial colonization is the species richness and evenness of the resident soil microbial community.It has been observed that resident microbial communities with higher diversity can better resist the alterations in community function and structure due to micr obial inv asions (Mallon et al. 2015 ) and that despite the outcome of the colonization, a legacy effect remains detectable in the niche structure of the community (van Elsas et al. 2012 ).
To impr ov e the efficacy of micr obial inoculants, r esearc h has focused on understanding the ecological interactions between inoculated microbes and the recipient ecosystem.Variable results hav e been r eported in differ ent studies r egarding the impact of inoculants on resident soil microbial communities, depending on the studied system, the sampling pr ocedur e, and the detection method used (e.g.cultur e-dependent, micr oscopy, or meta genomic) (Romano et al. 2020 ).Although there is little consensus about the degree of such effects (Trabelsi and Mhamdi 2013 ), a r ecent meta-anal ysis r eported that out of 108 studies on the impact of inoculation on resident microbial communities, 86% altered the soil communities either on the short or long term (Maw ar da et al. 2020 ).The majority of the reported studies assessed the impact of microbial inoculation on plant growth, biocontrol of plant pathogens, or plant tolerance to abiotic stresses suc h as dr ought or soil contamination (Maw ar da et al. 2020 ).Howe v er, the studies about the impact of div erse micr obial inoculants are still biased to w ar d single bacterial strains: out of the 108 studies, 86 assessed the impact of single bacterial inoculants, 22 of fungal inoculants, and only two studies of microbial consortia (Maw ar da et al. 2020 ).Fewer studies focused on microbialinduced systemic resistance (ISR), especially regarding resistance to insect pests.ISR-triggering microbes induced physiological and metabolic changes in the plant that result in an enhanced defense status against both biotic and abiotic stresses (Pieterse et al. 2014, Jeon et al. 2022 ).Microbial inoculation can impact the natur al comm unities not onl y thr ough micr obe-micr obe inter actions such as niche and nutrient competition, antibiosis, or priority effects (Fukami 2015 ) but also via altering the plant's physiology, and ther efor e plant's ecological inter action with the rhizospher e microbiota.
The plant's interaction with microbial inoculants is contextdependent, and the outcome of the mutualistic interaction can vary depending on the plant's physiological status (Lee Díaz et al. 2021 ).Abov egr ound or ganisms, suc h as insect pests, can impact belowground plant defense (alteration of root exudates and defense compounds) and the soil community composition (Bezemer and van Dam 2005 ).Under foliar insect herbivory stress, plants wer e r eported to inter act with the rhizospher e micr obiota and r ecruit micr obes that can help alleviate or fight the stressor (Yi et al. 2011 ).Se v er al studies hav e shown that both abov egr ound and belowground herbivory stress can induce changes in the rhizospher e micr obial comm unities (Hu et al. 2018, Pineda et al. 2020 ).The subsequent recruitment and assembly of the rhizospher e ar e lar gel y driv en by metabolic c hanges in r oot exudates and volatile compounds (Rizaludin et al. 2021 ).Howe v er, how microbial inoculation can impact plant chemistry and concomitantl y comm unity assembl y under str ess has r eceiv ed less attention.Plants' volatile emissions can vary according to their physiological status; e.g.stress or flo w ering, and abov egr ound str esses can have an impact on the root compartment.This has been shown in studies where leaf herbivor e-str essed plants presented a differ ent r oot volatilome than nonstr essed plants (Danner et al. 2015, Lee Díaz et al. 2022 ).Microbial inoculants and soil microbes can also emit volatiles in response to environmental factors such as plant hormones, nutrient r esources, and micr obe-micr obe inter actions (Sc hulz-Bohm et al. 2015 ).Assessing the impact of microbial inoculation not only from a community composition perspective but also from a metabolomic perspective will provide a mor e compr ehensiv e understanding of the untar geted inoculation effects (Maw ar da et al. 2020 ).
In this study, we investigated the impact of five microbial inoculant treatments on the resident rhizosphere microbial communities and the volatilome of tomato ( Solanum lycopersicum ) plants under leaf herbivory stress.We inoculated tomato plants with each of two phylogenetically diverse bacteria species; Bacillus amyloliquefaciens (Ba) and Pseudomonas azotoformans (Pa), and two fungal species; Trichoderma harzianum (Th) and Rhizophagus irregularis (Ri) to investigate common or inoculant-specific patterns on their impact on the r esident micr obial comm unities and the r oot volatilome.In addition to being inoculated alone as single species, the microbes were inoculated as a consortium or synthetic com-munity (SynCom) to test whether the combination affects the natur al comm unities differ entl y than single str ains.To compar e the inoculation effect under stress, a set of the inoculated plants was subjected to continuous leaf herbivory stress for 15 days by the c he wing lepidopter an insect Spodoptera exigua .Additionall y, we studied the root volatilome under differential control and stress conditions to assess changes in root chemistry during the first 24 h of the herbivory attack.Our study r e v ealed that the different microbial inoculants impacted the rhizosphere communities in terms of diversity and structure and also in terms of rhizosphere volatilome in a pr edominantl y unique manner.

Microbial strains and preparation of the inoculants
Micr obial str ains wer e pr o vided by K oppert (Berkel en Rodenrijs , the Netherlands); the bacterial str ains wer e (Ba) B. am yloliquef aciens strain CECT 8238 and (Pa) P. azotoformans F30A, while the fungal strains were (Th) T. harzianum T22 and the arbuscular mycorrhizal fungi R. irregularis (Ri) MUCL 57021.All inoculants were pr epar ed according to Minc he v et al. ( 2021 ).Bacillus am yloliquef aciens w as gro wn in tryptone so y a agar (TSA) at 28ºC for 24 h.For spor e pr oduction, liquid difco sporulation medium was pr epar ed as described by Nicholson and Setlow ( 1990 ) and inoculated with a single colony from TSA culture and incubated for 48 h at 28ºC with r otatory shac king at 200 r/m.The r esulting spor es wer e separ ated from the liquid medium by centrifuging for 15 min at 5000 r/m and resuspended in sterile tap water at a final concentration of 1 ×10 7 spores/ml.Pseudomonas azotoformans was grown on TSA at 28ºC for 24 h.Next, a liquid pr ecultur e was pr epar ed with tryptone so y a broth (TSB) inoculated with a single colony from TSA culture and incubated overnight at 28ºC with rotatory shaking at 200 r/m.Then 1 ml of pr ecultur e was used to inoculate 25 ml of TSB and incubated at 28ºC with rotatory shaking for 3 h when the bacterial growth is in the exponential phase.Bacterial cell concentration was quantified by measuring the optical density (OD) at 620 nm, then the cells were separated from the medium ( Table S1 , Supporting Information ) by centrifuging for 15 min at 5000 r/m and resuspended in tap water at a final concentration of 1 ×10 7 cfu/ml.Trichoderma harzianum was grown on potato dextr ose a gar at 25ºC for 7 da ys .Spor es wer e r ecov er ed fr om the sporulated culture in sterile tap water, spore concentration was quantified using a Neubauer hemocytometer and adjusted to a final concentration of 1 × 10 7 spores/ml.Rhizophagus irregularis was grown in monoaxenic culture on minimal (M) medium (Bécard and Fortin 1988 ) with Agrobacterium rhizogenes transformed carrot roots as host (St-Arnaud et al. 1996 ).Spores were extracted from sporulated culture and resuspended in tap water to a final concentration of 1000 spores/ml.Finally, a synthetic microbial consortia (SynCom) inoculum was pr epar ed mixing micr obial suspensions of 1 ×10 7 spores/ml of B. amyloliquefaciens , P. azotoformans , T. harzianum, and 1000 spores/ml of R. irregularis .

Soil prepar a tion, seedling inocula tion, and plant growing conditions
The soil was obtained from an olive tree field in Gójar with ann ual organic man ure fertilization under the trees (Granada, Spain) (37 • 05 49.5"N; 3 • 36 19.1 W; 810 m ele v ation).The soil used was a calcareous cambisol obtained by digging at a depth of 25 cm in the inter-rows between trees.Collected soil was sie v ed thr ough a 1.5-mm pore-diameter and tyndalized in thr ee consecutiv e days at 95 • C for 45 min (Tyndall 1877 ).The gr owing substr ate consisted of a mixture of tyndalized soil and sterile sand in proportion 1:1 v/v.Finally, 300 ml pots were filled with the growing substrate.
Seed surface sterilization, germination, and microbial inoculation were done according to Minc he v et al. ( 2021 ).Briefly, tomato Solanum lycopersicum cv Moneymaker seeds obtained from Vr eeken's Zaden (Dordr ec ht, the Netherlands), were surface sterilized by immersion in 5% sodium hypochlorite for 10 min, rinsed with sterile water three times for 10 min and incubated in sterile vermiculite for 7 days at 24ºC.Seedlings were root inoculated by pipetting 1 ml of a microbial suspension of eac h micr obe and the consortium during transplantation.A total of 72 plants were gr own: 12 r eplicates wer e inoculated per micr obial tr eatment with the corr esponding micr obial solution (Ba = B. am yloliquef aciens , P a = P. azofotormans , Th = T. harzianum , Ri = R. irregularis , and Syn-Com = synthetic comm unity).Similarl y, 12 contr ol plants wer e mock-inoculated with sterile tap water.All plants were grown under same conditions for 6 weeks in greenhouses at 24-20 • C (daynight) and r elativ e humidity of 60%.Plants wer e water ed twice per week with water and once per week with Long Ashton nutrient solution (Hewitt 1966 ) with reduced phosphate concentration (50%) to facilitate mycorrhizal establishment.After the completion of 6 weeks of growth, half of the plants per treatment were subjected to herbivory stress for another 2 weeks (further details in herbivory stress induction section), therefore final harvest was carried out at week 8 of growth for shoot biomass, shoot nutrient content, rhizospher e comm unities and micr obial colonization.

Herbivory stress induction
Spodoptera exigua (Lepidoptera, Noctunidae) eggs provided by Entocar e (Wa geningen, the Netherlands), wer e r ear ed after hatc hing at room temperature ( ∼21 • C) on an artificial diet ( Table S1 , Supporting Information ).For eac h micr obial tr eatment, six out of the 12 microbial-inoculated 6-week-old tomato plant plants were subjected to herbivory by placing third-instar larvae in a clip cage (stressed plants; H + ), while an empty clip-cage was placed in the remaining six nonstressed (H −) control plants per treatment.Two cater pillars wer e placed inside a clip ca ge on the a pical leaflet of the third true leaf and moved to another leaflet of the same leaf before the leaflet was fully consumed.Caterpillars were checked e v ery 48 h and dead cater pillars wer e r e placed to contin ue the herbivory stress for 2 weeks until the harvesting of the plants (at final stage of 8 weeks).

Micorrhizal colonization detection
Mycorrhizal colonization in Ri, SynCom and noninoculated plants was quantified histoc hemicall y.Upon harv esting, r oots wer e washed, cut into pieces of 1 cm and cleared by incubating them in 10% potassium hydroxide at 4ºC for 2 da ys .After clearing, root samples were rinsed three times with deionized water, acidified with 2% acetic acid for 5 min at room temperature and stained by immersion in a solution of 5% ink (Lamy, Germany) and 2% acetic acid for at least 30 min at r oom temper atur e .T he excess of ink solution was r emov ed by rinsing the root samples three times with deionized water (García et al. 2020 ).Mycorrhizal colonization was e v aluated b y quantifying the per centa ge of r oot length colonized by the fungus according to the grid line intersection method (Giovannetti and Mosse 1980 ) under stereo microscope Motic SMZ.Briefly, ar ound 200 r oot pieces wer e r andoml y placed in a Petri dish with grid of lines of 1 cm and mycorrhizal colonization was assessed by counting positi ve (m ycorrhizal) and negati ve (nonm ycorrhizal) roots/gridline intersections, counting between 100 and 200 intersections.Finally, the percentage of root length colonized by the fungus was calculated by dividing the number of positive intersections by the total number of intersections and m ultipl ying by 100 (García et al. 2020 ).

Plant nutrient content analysis
Leaf material was oven dried at 60 • C and separated from stems and br anc hes manuall y.Leav es wer e crushed in a mortar and further ground in the Tissue Lyser II (Qia gen, German y) inside a 2-ml Eppendorf tube with metal beads at a maximum speed for 3 min.An av er a ge of 2.2 mg aliquot w as w eighed per sample and folded in tin cups for analysis of carbon (C) and nitrogen (N) content in the Flash 1112 Elemental Analyzer (Thermo Scientific, MA, USA).C, N, and C/N ratio data were provided in μg and normalized according to sample weight (in mg).

Rhizosphere soil DNA extraction and sequencing
Rhizosphere soil was collected from root-attached soil of 8-weekold plants.Sterile vials of 15 ml were filled with soil adhering around fine roots from the bottom of the pot.Soil samples were frozen in liquid nitrogen and stored at −80 • C until further analysis.An aliquot of ∼806 ± 0.1 mg of each soil sample was used for DNA extraction and fine roots were removed manually with sterile utensils.Rhizospheric DNA extraction was done according to the manufacturer's instructions with the DNeasy ® Po w erSoil ® Pro Kit (Qiagen, Hilden, Germany).DNA quantity and quality were measur ed with NanoDr op ® and Qubit ® fluor ometers.DNA samples were sequenced using the Illumina NovaSeq6000 or MiSeq system and demultiplexed by BaseClear N.V. (Leiden, the Netherlands).For bacteria, the V3-V4 region of the ribosomal (rRNA) 16S gene was amplified with the 341F-NXT/785R-NXT primers.For fungi, internal transcribed spacer (ITS) in the ribosomal (rRNA) gene was amplified with the ITS86F/ITS4 primers according to Beeck et al. ( 2014 ).Sequencing yielded an av er a ge of 33 416 bp read pairs for fungal sequences and 38 369 bp for bacterial sequences .T he a verage quality was 34.7 and 34.3 for fungal and bacterial sequences, r espectiv el y.

Vola tile tr apping and da ta anal ysis
Rhizosphere volatiles were trapped through passive diffusion by placing one Tenax ® (Markes International, Llantrisant, United Kingdom) tr a p containing 200 mg T enax/tube type T A 60/80tr a p inside a metal holder in eac h pot, r eac hing an a ppr o ximate de pth of 5 cm.Metal holders were stainless steel cylinders with perforations allowing the air entrance while protecting the trap from soil contamination.Tenax tr a ps wer e placed befor e the onset of the herbivory stress for 24 h (T0).Upon the leaf-herbivory stress induced by S. exigua , new Tenax traps were placed in the same pots where T0 was measured.Traps were placed 24 h after the onset of the herbivory stress for a 24 h period, thus collecting the volatiles during the initial 24-48 h herbivory stress induction period (T1).Tr a ps wer e tightl y closed and stored at r oom temper ature until measurement.Before utilization, Tenax traps were preconditioned by heating at 300 • C for 45 min under helium flow (5 l/min).
Full details of Tenax measurement regarding thermal desorption, GC/Q-T OF measuring conditions , calibr ation, data anal ysis, and compound identification are described by Lee Díaz et al. ( 2022 ).Briefly, v olatiles w as thermo-desorbed fr om Tenax tr a ps at 240 • C for 8 min and then tr ansferr ed to an ultra-inter column (122-5532 UI, Agilent Tec hnologies, Inc., Santa Clar a, CA, USA) of the GC/Q-TOF (model Agilent 7890B GC and the Agilent 7200A Q-TOF).An n-alkane (C8-C20) standard solution was spiked at the beginning of the run for calibration.Mass spectra of compounds were acquired in full-scan-mode and GC/Q-T OF ra w data was translated to .cdfformat and analyzed with MzMine v2.53 (Pluskal et al. 2010(Pluskal et al. , 2020 ) ) for mass feature detection and peak intensity quantification.P ar ameters used for GC-MS peak intensity tables (Du et al. 2020 ) ar e av ailable in Table S3 ( Supporting Information ).Peak intensity tables were used in combination with c hr omatogr am data (Mass Hunter Qualitative v10, Ag ilent Technolog ies) for manual identification of volatile compounds comparing the mass spectrum of target compounds with the NIST 2020 database (V2.20,National Institute of Standards and Technology, USA).

Sta tistical anal ysis
Statistical analysis on nutrient data was done with RStudio version 2022.07.2 + 576.2-way ANOVA analysis with sums of squares type III was applied to C, N, and CN r atio r elativ e v alues for differences between microbial treatments and herbivory stress.Post hoc analysis was applied with the Tuk e y Honest Significant Difference (HSD) test.Interaction figures elaborated with the emmeans pac ka ge fr om a linear model test for inter acting factors.
Statistical analysis of amplicon sequence data of ASV abundance and taxonomy tables were statistically analyzed with the ph yloseq (McMur die and Holmes 2013 ) and metagenomeSeq (Paulson et al. 2013 ) R pac ka ges for r elativ e abundance, alpha, and beta div ersity, and ASV contr ast anal ysis of bacterial and fungal comm unities.Alpha div ersity indexes Shannon, Chao1, Observed, and Inverse Simpson (InvSimpson) were calculated with the es-timate_richness function of the phyloseq pac ka ge.Statistical analyses of diversity indexes were done applying a tw o-w ay ANOVA test with microbial treatment (with six levels for Control, Ba, Pa, Th, Ri, and SynCom) and herbivory stress (with two le v els for nonherbivory control and herbivory-stressed) as factors.Post hoc analysis was performed with Tuk e y-HSD.Kruskal-Wallis statistical test was applied when data were not normally distributed.Beta diversity was calculated over normalized ASV counts with the cum ulativ e sum scaling (CSS) cumNorm function of the phyloseq pac ka ge .T he distance matrix was built according to the Bray-Curtis method, and Perm utational m ultiv ariate anal ysis of v ariance (PERMANOVA) analysis was done with the adonis function of the vegan pac ka ge and the post doc test with the pairwise.adonispac ka ge at 9999 perm utations.Contr ast anal ysis of ASV differ ential abundance was done with the metagenomeSeq pac ka ge.CSSnormalized samples were filtered for estimated effective samples and fitted for differential testing with the fitZig function.Contrast matrixes wer e compar ed pairwise to obtain ASVs with a logarithmic FC statistically significant ( P -value < .05).ASV differential analysis representations were elaborated with Fluorish Studio ( https:// flourish.studio/).
Statistical analysis of peak intensity tables of volatile data was done with MetaboAnalyst v.5.0 (Pang et al. 2021 ).Peak intensity tables were analyzed with two different statistical tests; one to test the effect of the microbial inoculation on the volatilome of nonstressed or stressed plants (analysis one), and a second analysis to test the effect of the str ess within eac h micr obial tr eatment (anal ysis two).For anal ysis one, normalization was done by log10 transformation and P ar eto-scaling.Statistical differ ences between tr eatments wer e anal yzed with one-way ANOVA for timepoint T0 (nonstressed) and in a separ ate anal ysis for T1 (stressed).Post hoc analysis of Tuk e y's HSD was performed for pairwise comparisons between treatments of significantly different compounds.Data was r epr esented with a hier arc hical clustering as a heatma p. Tr eatment gr oup av er a ges wer e cluster ed according to Euclidean distance similarity measures according to W ard' s linka ge algorithm.For anal ysis tw o, normalization w as done b y log10 transform and autoscaling.Statistical differences within one treatment before and after herbivory wer e anal yzed with a paired Fold Change (FC) analysis.Paired (nonindependent data) FC analysis counts the total number of FCs above a threshold of 2 and v alues ar e pr ovided in the log2 scale.FC r epr esentation with bar plots was elaborated with R Studio version 2022.02.3 build 492.

Microbial colonization, plant biomass, and nutrient content
The presence of the microbial inoculants in the rhizosphere at 8 weeks after inoculation was confirmed by RT-qPCR, for all treatments (data not shown).In addition, root colonization by the introduced arbuscular mycorrhizal fungus R. irregularis was confirmed by histochemical staining of fungal structures within the roots .T he root mycorrhization percentage ranged from 20% to 50%, and differences between treatments were statistically significant.( Figure S1 , Supporting Information ).Under herbivory stress, Ri-inoculated plants had a significantly higher mycorrhization percenta ge than nonstr essed contr ol plants ( P -adj = 0.006) and SynCom-inoculated plants ( P -adj = 0.031).This result suggests a differ ent plant-AMF inter action when R. irregularis is inoculated as single species (Ri) or in a SynCom under leaf herbivory stress.
Accor ding to tw o-w ay ANOVA, microbial inoculation did not have an effect on plant shoot biomass.The herbivory stress led to a slight reduction on the shoot biomass of Ri-inoculated plants (Ri H + vs. H −; P -adj = 0.015) ( Figure S2 , Supporting Information ).The effect microbial inoculation on the r elativ e shoot nutrient content ( μg/mg), was herbivory-stress dependent, since two-way ANOVA sho w ed that the interaction between the inoculant treatment and the herbivory significantly impacted C, N, and C/N ratio (Tr eatment * Herbivory; C P -v alue = .02,N P -v alue = .002,and C/N P -value = .007)(Fig. 1 ).The herbivory stress altered the relative content of shoot C and C/N ratio, and a significant interaction between microbial treatment and herbivory stress was observed for all nutrient parameters (C, N, and C/N) ( Table S4 , Supporting Information ).Control-and Ba-inoculated plants presented a similar trend in N and C/N ratio in response to herbivory; for both tr eatments, N significantl y incr eased upon herbivory (and thereby a reduction of C/N ratio) ( Table S4 , Supporting Information ).Under herbivory stress , T h-inoculated plants sho w ed opposite, y et not statistically significant, nutrient responses for N and C/N r atio compar ed to Contr ol and Ba-inoculated plants (Fig. 1 ).Interestingly, the nutrient content in SynCom-inoculated plants was bar el y alter ed b y herbiv ory stress (Fig. 1 ).
The m ultiv ariate principal coordinates anal ysis (PCoA) sho w ed absence of clustering of treatments, with an ov erla p between stressed and nonstressed communities (Fig. 2 B).Tw o-w ay ANOVA analysis sho w ed that bacterial alpha diversity w as significantly impacted by microbial inoculation (F-value = 4.25, P = .002)and herbivory str ess (F-v alue = 6.31,P = .015).The microbial inoculation effect was statistically significant only in nonstressed plants, wher e Contr ol and P a-inoculated plants had a higher Shannon index than Th-inoculated plants (Fig. 2 C).The herbivory stress caused an ov er all significant increase in alpha diversity, but no significant differences among treatments were observed (Fig. 2 C).Despite the herbivory stress having a general effect on div ersity, onl y Pa-inoculated plants sho w ed a reduction of the Shannon index under stress (Fig. 2 D).An additional description of rhizobacterial alpha diversity values (Chao1, Observed, and Inverse Simpson indexes) and statistical analysis performed on pairwise differences between treatments under different stress levels are provided in Table S5 ( Supporting Information ).
Contr ast anal ysis of ASV's r elativ e abundances confirmed that Ba-and Th-inoculated plants had the largest number of significantl y r educed ASVs compar ed to noninoculated Contr ol plants.In absence of herbivory, 39 out of the 48 differ entiall y abundant ASVs between Control and Ba-inoculated plants were significantly r educed in contr ol plants (Table 2 ).T he T h was the second inoculant with the most differ ential ASVs, wher e 19 ASVs were reduced upon inoculation (Table 2 ).Similarly, under stress, Ba and Th treatments also accounted for the largest number of differential ASVs (50 and 56, r espectiv el y).The r emaining tr eatments pr esented a higher number of differential ASVs in comparison with the Control under herbivory stress: 36 for SynCom-, 34 for Ri-, and 35 for Pa-inoculated plants (Table 2 ).Overall, the number of enriched ASVs r elativ e to the Contr ol w as higher under herbiv ory stress.

Fungal communities
Fungal comm unities pr esented a total of 1989 ASVs comprised of 10 phyla, 245 genera, and 290 species .T he phylum Ascomycota was the most dominant, r epr esenting 92% of the fungal r elativ e abundance, follo w ed b y Basidiomycota (4%), Glomeromycota (2%), Chrytidiomicota (1%), and Mortierellomycota (1%).Within the Ascomycota, the five most abundant classes w ere Sor dariom ycetes (49.5%),Dothiedeom ycetes (17.4%),Pezi-zom ycetes (11.6%),Eurotiom ycetes (9.5%), and Leoteiom ycetes (3.7%) (Fig. 4 A).Of the 290 identified species, Fusarium clamydosporum accounted for 30% of the fungal r elativ e abundance, follo w ed b y three main species; Preussia terricola (6%), Alternaria subcucurbitae (5.2%), and Stac hybotrys c hartarum (5%).Onl y 33 species pr esented a r elativ e abundance higher than 0.5%.PERMANOVA test indicated that onl y micr obial inoculation significantly impacted the communities but not the herbivory stress (Table 3 ).Post hoc pairwise tests between microbial treatments sho w ed that all microbial inoculants significantly impacted the beta diversity in comparison to noninoculated Control plants (Table 3 ).Also, Syn-Com's beta diversity significantly differed from Ba-, Pa-, and Thinoculated plants, showing a different effect of these three microbes when inoculated as single species.A pairwise comparison of communities of each treatment at different stress conditions sho w ed that only Ba-inoculated plants were significantly altered by the herbivory stress (Ba H − vs. H + ) (Table 3 ).Multiv ariate anal ysis sho w ed a lo w separ ation among tr eatments despite the differences in microbial communities due to microbial inoculation confirmed by PERMANOVA analysis.Howe v er, an ov erla p between str essed and nonstr essed comm unities w as sho wn for fungal communities (Fig. 3 B).Although a similar trend as in bacterial diversity was observed for fungal alpha diversity, neither the overall impact of microbial inocula-tion nor herbivory stress was statistically significant ( Table S6 , Supporting Information ).Ho w e v er, under no str ess conditions, only SynCom-inoculated plants had a significantly higher alpha diversity than the control (Fig. 3 C).Although herbivory stress did not have an ov er all effect on fungal alpha diversity, in noninoculated Control plants a significant increase was observed under herbivory stress (Control H + vs. H −; P = .004)(Fig. 3 D).A com- plete description of bacterial Shannon index values and additional statistical analysis performed on pairwise differences between treatments under different stress levels for Chao1, Observ ed, and inv erse Simpson indexes ar e pr ovided in Table S7 ( Supporting Information ).
Similar to alpha diversity results, there was no microbial inoculation or herbivory stress pattern in fungal ASV contrast analysis.All microbial treatments presented a similar number of enriched and reduced ASVs compared to noninoculated control plants both with and without herbivory stress (Table 4 ).While ther e wer e no commonl y r educed fungal ASVs, thr ee fungal species were commonly enriched in all treatments with respect to contr ol, r egardless of the str ess; ASV6 Fusarium oxysporum (Sordariomycetes), unknown ASV48 (Sordariomycetes) and unknown ASV23 ( Figure S5 , Supporting Information ).Under no herbivory, two fungal species wer e commonl y enric hed in all micr obial tr eatments; ASV163 Schizothecium fimbriatum (Sordariomycetes) and ASV172 Clareoideoglomus walker (Glomeromycotes).In particular, Ba-inoculated plants sho w ed significant enrichment of two Aspergillus spp.(Eurotiomycetes) ASVs; ASV11 and ASV12.Under herbivory stress, In addition to F. oxysporum , ASV48, and ASV23, another three ASVs were commonly enriched in all treatments with respect to control ( Figure S6 , Supporting Information ).Two w ere Sor dariomycetes (ASV210 Neocosmospora rubicola and ASV7 Kernia columnaris ) and one unknown ASV7.Only one ASV29 Plectosphaerella cucumerina (Sordariomycetes) was commonly reduced in all treatments compared to the control ( Figure S6 , Supporting Information ).

Impact of microbial inoculation on the rhizosphere volatilome
Volatiles from roots inoculated with the six microbial inoculant tr eatments wer e compar ed befor e (T0) and 24 h after (T1) leaf herbivory stress by S. exigua .A total of 24 volatile compounds were detected across treatments (Table 5 ).The volatiles belonged to nine chemical classes: alcohol, aldehyde, alkane, aromatic, carboxylic acid, furan, monoterpene, a sulfur compound, and thiazole .One-wa y ANOVA of each volatile compound showed that microbial inoculation had a significant impact on six compounds; acetic acid, benzene acetaldehyde, decanal, dimethyl disulfide, and two unknown compounds (954 and 985) (Table 5 ).The av er a ge peak intensity of unknown compound 954 was significantly higher in bacterial-inoculated treatments (Ba and Pa) and noninoculated contr ol, wher eas decanal and benzene acetaldehyde were higher in fungal-inoculated treatments (Ri, Th, and SynCom).
Hier arc hical clustering according to Euclidean distances of tr eatment av er a ges sho w ed that fungal inoculated treatments (Ri, Th, and SynCom) grouped, while the bacterial treatments were more similar to noninoculated Control plants (Fig. 4 ).Interestingl y, after the str ess induction, one-way ANOVA anal ysis sho w ed that no volatile compounds were found to be significantly different among treatments .T herefore , the hierarchical clustering of tr eatment av er a ges did not group according to the micr obial tr eatment, ther efor e the SynCom did not cluster together with the rest of the fungal treatments (Ri and Th) (Fig. 4 ).
FC analysis of the value change between subsequent measurements sho w ed significant changes in all tr eatments befor e and after herbivory stress, with an increase of two volatile compounds in all treatments: benzothiazole and dimethyl disulfide (DMDS).The majority of significantl y differ ent compounds increased under herbivory stress with respect to the control condition (Fig. 5 ).The classes of stress-enhanced compounds were mainly sulfur, alkane , aldehyde , benzene , fur an, and monoter pene.Dimethyl trisulfide (DMTS) significantl y incr eased under str ess in all tr eatments except for Th.A pattern was shown between bacterial and Ta ble 5. Tomato rhizosphere v olatilome under microbial inoculation and herbiv ory stress.List of all v olatile compounds detected in tomato rhizospher es fr om both contr ol and inoculated plants with and without herbivory stress.Volatile compounds are classified according to chemical class and sorted by calculated retention index according to HP-5 column type (RI cal) and contrasted to liter atur e (RI lit).Statistical analysis output provided for differences between microbial treatments under nonherbivory conditions (control; C, B. am yloliquef aciens ; Ba, P. azotoformans ; Pa, T. harzianum ; Th, R. irregularis ; Ri, and synthetic community; SynCom).fungal inoculants: bacterial inoculants (Ba and Pa) together with control plants sho w ed an increase of alkanes and aldehydes; either from hexanal, octanal, octane, nonanal, nonane, or decanal.The fungal inoculants (Ri, Th, and SynCom) shared a FC increase of monoter penes suc h as p-cymene and limonene.P articularl y, Ri-inoculated plants were the only ones presenting a fold-increase of the two furan compounds benzofuran and 2-pentyl furan.Decr eased FC compounds wer e differ ent acr oss all tr eatments .T he Th treatment sho w ed the largest number (four) of reduced compounds under herbivory (Fig. 5 ).

Discussion
Our study aimed to understand the impact of bacterial and fungal inoculants on the rhizosphere microbiota composition and volatilome of tomato plants under herbivory stress.First, we hypothesized that microbial inoculants would impact both the rhizospher e micr obial comm unity composition and the rhizospher e volatilome.We r e v ealed that the individual bacterial and fungal inoculants and the SynCom had distinctive impacts on the rhizospher e micr obiome composition differing among themselves and in comparison, to the noninoculated control plants.Also, rhizosphere volatiles were impacted upon inoculant treatment, showing eac h micr obial inoculant tr eatment a unique blend of volatile compounds among themselves and compared to control plants.
Next, we hypothesized that the addition of a continuous leaf herbivory stress to a plant-microbial inoculant system would impact the relationship of the plant and the microbial inoculants both at rhizospher e micr obiome and volatilome le v el.We confirmed that herbivory stress had a general effect irrespective of the inoculant type for the majority of measured parameters on rhi-zospher e micr obiome composition, although some effects were stress-inoculant specific.Also, under herbivory each microbial inoculant presented different volatile blends compared to their previous nonstressed condition.Our study confirmed that the effects of the five different microbial inoculants and the microbial consortium on plant physiology can be general or stress-dependent.
There was not major impact on plant physiology tr aits suc h as shoot nutrient content or biomass due to the inoculation.Howe v er, we observ ed that herbivory had a gener al significant effect on leaf nutrient content and a micr obe-dependent incr ease of N in noninoculated control and Ba-inoculated plants .T hese two treatments sho w ed a significantly higher r elativ e amount of shoot N (ther efor e a significantl y differ ent C/N r atio) under herbivory stress .T he increase in N in the shoot might be related to the mobilization of amino acids for the synthesis of defense-related compounds (Zhou et al. 2015 ).Complementary analysis on the pest r elativ e gr o wth or feeding performance w ould be necessary to determine the positive or negative impact on the pest of the N increase.Regarding the shoot biomass, neither the inoculants nor the herbivory had a significant effect, except for Ri-inoculated plants, where a significant reduction of shoot biomass was observ ed under herbivory.Similarl y, further studies on the pest performance might help clarify whether the biomass reduction is caused due to higher consumption rate by the pest or a growthdefence trade-off (Züst and Agrawal 2017 ).Overall, these results indicate that the impact of microbial inoculants and the herbivory stress was unique for each plant-microbial inoculant-stress combination, indicating a certain le v el of specificity in each tripartite plant-micr obe-insect inter action.Amplicon sequencing analysis of rhizosphere soils sho w ed that all microbial inoculants and the herbivory stress impacted differ entl y the bacterial and fungal communities in terms of diversity and structure.Bacterial alpha diversity was impacted by the microbial inoculants only under no-stress conditions .T he div ersity of B. am yloliquef aciens (Ba)-and T. harzianum T22 (Th)inoculated plants were the lowest compared to control.It is unclear whether these inoculants dir ectl y competed with the local microbiota altering the rhizosphere through microbe-microbe inter actions, or indir ectl y alter ed the plant's physiology through ISR activation.It has been shown that the coinoculation of Bacil-lus spp.-and T. harzianum -induced changes in the rhizosphere cr eating a suppr essiv e envir onment a gainst a pathogenic Fusarium strain (Xiong et al. 2017 ).On the other hand, inoculated microbes can alter the plant's phytohormone balance and affect the plant's responses to later colonizers (Toju et al. 2018 ).Ho w e v er, such effects on the alpha diversity were no longer observed upon leaf herbivory stress .Abo veground stresses can cause dramatic changes in plant physiology leading to differential microbial recruitment via changes in root exudates and volatiles (Yi et al. 2011 ).Although the alpha diversity was overall increased under str ess, all tr eatments sho w ed similar le v els of div ersity, indicating that the herbivory nullifies or e v ens the effect of the individual inoculants.Although bacterial comm unities wer e dominated by Actinobacteria and Proteobacteria, among other phyla typically reported as rhizosphere-associated bacteria (Trivedi et al. 2020 ), differences in relative ASVs abundance between treatments compar ed to contr ol wer e mor e pr onounced under str ess.Inoculants Ba and Th presented the largest number of differentially abundant ASVs with respect to noninoculated control plants (both with and without herbivory).Under nonstress conditions, they sho w ed a common reduction with respect to noninoculated control plants of the actinobacterium Cellulomonas spp., which has been pr e viousl y r eported to be highl y associated with tomato landr aces typical from southern Spain (Smulders et al. 2021 ).Together with the SynCom, these thr ee tr eatments pr esented a common enric hment of diverse bacterial genera; Blastococcus spp.(Actinomycota) has been reported in the rhizosphere of tomato plants adapted to arid, desert, or stone environments (Sghaier et al. 2016 ), and Ramilibacter spp.(Pseudomonadota) and Ohtaekwangia spp.(Bacter oidetes) wer e r eported in gr a pe vine fields r elated to unfarmed soils or r ecentl y farmed soils (Liu et al. 2021 ).Ho w e v er, the r ole these micr obes hav e in association with tomato plants is still unkno wn.Under herbiv ory str ess, a gener al herbiv ory effect w as observed since a higher number of ASVs were commonly enriched among micr obial tr eatments compar ed to noninoculated contr ol plants .T his indicated that the microbial recruitment upon stress was not impaired or reduced by the micr obial tr eatments, but had a different recruitment outcome than in noninoculated control plants.Ho w ever, most of the commonly recruited microbes by the treatments under stress were unknown ASVs .T he beta diversity of bacterial communities was more affected by the microbial treatments .T he ASVs recruited under stress may be part of the r ar e rhizospher e micr obiome, whic h is known to hav e an important role in microbial communities despite its low r elativ e abundance (Jia et al. 2018 ).
Fungal alpha diversity was generally not affected by microbial inoculation or herbivory.Although a trend was visible like in bacterial alpha div ersity, onl y under contr ol conditions ther e ar e differences between treatments that are no longer detectable under stress.Under no stress, SynCom was the treatment with the highest alpha div ersity.Similarl y, SynCom sho w ed the most different fungal communities with respect to control.Beta diversity of fungal communities was largely affected by the microbial inoculation regardless of the stress.In general, fungal communities were dominated by Ascomycota (more than 90% r elativ e abundance), in particular by the Sordariomycetes order, and the single species Fusarium c hlam ydosporum accounted for one-third of the r elativ e abundance.Like many other Fusarium spp.endophytic strains that hav e been r eported to be beneficial to plants (P a ppas et al. 2018 , de Lamo and Takken 2020 , Toghueo 2020 ), F. c hlam ydosporum can be a nonpathogenic fr ee-living str ain with necr otr ophic behavior (Torbati et al. 2021 ).Inter estingl y the Ba-inoculated plants presented a larger abundance of Aspergillus spp.under no-herbivory conditions than under herbivory stress.Plants can shift from one microbial partner to another under stress (Zuccaro 2020 ) and it is possible that under herbivory stress some plant-microbe relationships might be altered.Although the Aspergillus species was unknown, it is possible that it was recruited for P-solubilization capacity (Khan et al. 2007 ) since the plants w ere w atered with a Plimited fertilization regime .T his general microbial-treatment effect was also observed in similar patterns in terms of ASVs r elativ e abundance.Microbial inoculation effects on fungal communities wer e gener al since all tr eatments had enric hment of F. oxysporum compared to control plants.It is possible that the microbial inoculation and stress had a systemic effect on the plant defenses and phytohormonal balance (Friman et al. 2021 ) that created a suitable niche for F. oxysporum (Constantin et al. 2019 ).In addition to F. oxysporum , other fungal species were commonly enriched in all treatments upon herbivory stress with respect to control.Three ASVs reported as unknown taxa, Kernia spp., which has been reported as a decomposer of herbivore dung (Caretta et al. 1998 ), and Neocosmospora rubicola , reported as both plant pathogen (Zheng et al. 2018, Riaz et al. 2022 ) and as plant endophyte together with other species from the genus (Kim et al. 2017, Sandoval-Denis et al. 2019 ).Ho w e v er, whether these fungal species benefit from the plant's stress condition or play an activ e r ole in helping the plant's defenses is unknown.In general, fungal effects are mainly dominated by microbial inoculation and are general, meaning that micr obial inoculants hav e less pr onounced individual effects .T he arid nature of the region where the soil was extracted could explain the high abundance of Fusarium species, known to thrive in desertic and extreme environments (Mandeel 2006 ).
Inoculated plants with the SynCom behav ed differ entl y than the other microbial treatments and the noninoculated controls.Individually inoculated Ba or Th reduced bacterial alpha diversity while SynCom-inoculated plants did not.Also, SynCom bacterial beta diversity was different from noninoculated control and to Baand T h-inoculated plants .For fungal communities , SynCom inoculated plants had higher alpha diversity and the beta diversity differ ed fr om contr ol and Ba-, P a-, and T h-inoculated plants .Howe v er, it is not clear what are the microbial interactions between the inoculated microbes or whether some microbes have a more pr edominant r ole than others.Plant shoot nutrient and biomass data indicated that SynCom did not have an additional effect.It is questioned whether microbial consortia translate into additional beneficial effects for the plants (Bradá čová et al. 2019b ).Microbial consortia are often reported to deliver better effects under stress (Bradá čová et al. 2019a, Joshi et al. 2020 ).
Microbial inoculants impacted the rhizosphere volatilome under the nonstress condition.Six volatiles were found to be different among treatments only by inoculation.All six compounds wer e significantl y higher in one or more fungal-inoculated treatments (Th, Ri, and SynCom).Inter estingl y, the SynCom behav ed mor e similarl y to the fungal inoculants Ri and Th in terms of rhizosphere volatilome .T h-inoculated plants sho w ed a high intensity of acetic acid, which might be related to the indole-3-acetic acid production reported in many Trichoderma strains as a r oot gr owth-pr omoting hormone (Nieto-Jacobo et al. 2017 ).Ri-inoculated plants sho w ed an increase in unknown 985 and SynCom-inoculated plants in DMDS.Upon stress, an ov er all volatilome change was observed with no volatile compound significantl y differ ent between tr eatments.Tw o compounds w ere commonl y incr eased in all tr eatments upon str ess: DMDS and benzothiazole.Both DMDS and benzothiazole have been reported as microbial volatiles with antifungal or antimicrobial properties.For example, DMDS has been shown to effectiv el y r educe F. oxysporum populations (P a pazlatani et al. 2016 ) while benzothiazole has antimicr obial functions a gainst pathogens (Gao et al. 2017, Lammers et al. 2021 ).It has been shown that abov egr ound herbivory can reduce the root volatile production of terpenes and increase the production of aldehydes and sulfur compounds (Lee-Diaz et al. 2022 ).Bacterial inoculants sho w ed similar patterns in v olatile enric hment upon str ess: by incr easing the pr oduction of sulfur compounds , aldehydes , and alkanes .Ho w e v er, fungal inoculants and the SynCom behaved similarly by increasing the production of terpenes , alcohols , and furans .Despite the similarities , each microbial inoculant had a unique "stress-enriched" volatilome; Riinoculated plants sho w ed enrichment in two furan compounds, whic h ar e mainl y pr oduced by fungi and hav e been r elated to antimicrobial functions (Farh and Jeon 2020 ), while Th-inoculated plants presented both increase and decrease of monoterpenes and furan compounds .T he unique stressed rhizosphere volatilome of each microbial treatment could have a further impact on ecological interactions with other soil trophic levels.For example, incr eased DMDS fr om str essed r oots has been shown to attr act natur al enemies of r oot-feeding herbivor es (Danner et al. 2015 ).Also, aldehydes have been reported as attractants to soildwelling insects, such as coleopteran larvae (Barsics et al. 2017 ).
Ov er all, our r esults sho w ed that abov egr ound herbivory affected the rhizosphere's volatile and microbiome composition.This stress-associated effect was impacted by microbial inoculation, and depending on the parameter measured (diversity, comm unity structur e , biomass , and colonization), the effects were common for all microbial inoculants or inoculant-specific.Ov er all, the impact of microbial inoculation was stronger under nonstress conditions .T he differences found in both community structure and volatilome wer e le v eled by herbivory, illustrating that biotic stress is a major driver of plant-microbe interactions.Ho w e v er, the unique inter action of micr obial inoculant-herbivorydependent effects reflects the complexity of the plant's ecological interactions and context dependency.Further knowledge on the ecological role of inoculants and their interactions with biotic and abiotic factors can bring knowledge that impr ov es their efficacy and safe application.

Figure 1 .
Figure 1.Impact of microbial inoculation and leaf herbivory stress on shoot C, N, and C/N content.Boxplots of relative shoot nutrient content ( μg/mg) of 8-week old tomato plants inoculated with microbial treatments Control (mock-inoculated), Ba, Pa, Th, Ri, and SynCom.Red color indicates plants without herbivory (H −), while plants subjected to herbivory stress over 2 weeks are indicated in blue (H + ).

Figure 2 .
Figure 2. Impact of microbial inoculation and herbivory on bacterial communities and di versity.Relati ve abundance (A), beta diversity (B), and alpha diversity (C) and (D) of tomato rhizobacterial communities per microbial treatment; noninoculated (Control), B. amyloliquefaciens (Ba), P. azotoformans (Pa), T. harzianum T22 (Th), R. irregularis (Ri), and the SynCom, with (H + ) and without herbivory (H −) stress.(A) Bar plot of bacterial phyla r elativ e abundance grouped by microbial inoculant treatment.Each stacked bar represents the average relative abundance of the different taxa (color guide on the legend) according to the herbivory stress (the left bar for H −; nonstressed, the right bar for H + ; herbivory-stressed). (B) Principal Coordinates Analysis (PCoA) plot of Euclidean distances representing community dissimilarities between treatments (color guide) and stress (circles for nonstressed, and triangles for stressed plants).The x -and y -axis r epr esent the components explaining the maximum variability between samples.Box plots of alpha diversity Shannon index for comparisons among microbial treatments within one stress condition (C) or within a microbial treatment (D).Statistical differences between comparisons ( P < .05)are noted with different letters (C).

Figure 3 .
Figure 3. Impact of microbial inoculation and herbivory on fungal communities and diversity.Fungal relative abundance (A), beta diversity (B), and alpha diversity (C) and (D) of tomato rhizosphere communities per microbial treatment; noninoculated (Control), B. amyloliquefaciens (Ba), P. azotoformans (Pa), T. harzianum T22 (Th), R. irregularis (Ri), and the SynCom, with (H + ) and without herbivory (H −) stress.(A) Bar plot of fungal classes r elativ e abundance grouped by microbial inoculant treatment.Each stacked bar represents the average relative abundance of the different taxa (color guide on the legend) according to the herbivory stress (the left bar for H −; nonstressed, the right bar for H + ; herbivory-stressed). (B) PCoA plot of Euclidean distances r epr esenting comm unity dissimilarities between tr eatments (color guide) and str ess (circles for nonstr essed, and triangles for stressed plants).The x -and y -axis represents the components explaining the maximum variability between samples.Box plots of alpha diversity Shannon index for comparisons among microbial treatments within one stress condition (C) or within a microbial treatment (D).Statistical differences between comparisons ( P < .05)were noted with different letters (C) or with an asterisk (D).

Figure 4 .
Figure 4. Impact of microbial inoculation on rhizosphere volatilome with and without herbivory str ess.Heatma ps of volatile compounds' peak intensity av er a ged ( n = 6) per micr obial tr eatment (Contr ol, Ba, Pa, Th, Ri, and SynCom).Left panel (A) compar es rhizospher e volatilomes among micr obial tr eatments without str ess (T0).Right panel (B) compar es rhizospher e volatilomes among micr obial tr eatments upon 24 h of leaf herbivory stress (T1).Compound peak intensity is indicated with a color gradient legend with dark blue as the lo w est intensity and dark red as the highest intensity.

Figure 5 .
Figure 5.Effect of leaf herbivory stress on rhizosphere volatilomes.Bar plots of significantly changed volatile compounds' peak intensities after 24 h of shoot herbivory stress within each microbial treatment.The dashed line indicates a 2-fold logarithmic change (log2 FC) peak intensity increase under herbivory stress with respect to the previous nonstressed condition.FC values next to horizontal colored bars for each compound; blue for increased compounds under herbivory and red for reduced compounds under herbivory).

Table 1 .
Bacterial beta diversity.PERMANOVA test v alues for the effect of micr obial inoculation and str ess on bacterial comm unities.Pairwise test values for differences between bacterial communities.P airwise Adonis v alues for comparisons between tr eatments (onl y statisticall y significant comparisons r eported for Contr ol and SynCom).P airwise comparison test values within treatment for comparisons of one microbial treatment between two stress conditions (nonstr essed; H −, herbivory-str essed; H + ).Onl y significant comparisons are reported. 1

Table 2 .
Bacterial ASVs differential relative abundance.Total numbers of significantly reduced or enriched (fold-changed) ASVs under nonherbivory (H −) or leaf-herbivory stress (H + ) in control plants with respect to the compared microbial treatment.

Table 3 .
Fungal beta div ersity.PERMANOVA test v alues for the effect of microbial inoculation and stress on fungal comm unities.P airwise test values for differences between fungal communities.